big data

Businesses who have lived through the evolution of the digital age are well aware that we’ve
experienced a generational shift in technology. The rise of software as a service (SaaS),
cloud, mobile, big data, the Internet of Things (IoT), social media, and other technologies
have disrupted industries and changed customers’ expectations. In our always-on, buy
anything anywhere world, customers want their shopping experiences to be personalized,
dynamic, and convenient.
As a result, many businesses are trying to reinvent themselves. Success in a fast-paced
economy depends on continually adapting and innovating. Companies have to move quickly
to keep up; there’s no time for disjointed technologies and old systems that don’t serve the
customer-obsessed mentality needed to thrive in the digital age.

With the opportunity to leverage new analytic systems for Big Data and Cloud, companies are looking for ways to deliver live SAP data to platforms such as Hadoop, Kafka, and the Cloud in real-time. However, making live production SAP data seamlessly available wherever needed across diverse platforms and hybrid environments often proves a challenge.
Download this paper to learn how Attunity Replicate’s simple, real-time data replication and ingest solution can empower your team to meet fast-changing business requirements in an agile fashion. Our universal SAP data availability solution for analytics supports decisions to improve operations, optimize customer service, and enable companies to compete more effectively.

Not long ago, the biggest concern for IT decision makers considering
moving workloads to the cloud was security. That’s no longer the case.
Today, the main obstacle to cloud adoption is different but familiar:
the pain of migrating data.

Hoarding data isn’t doing much to help your financial services firm if you can’t easily combine data from multiple sources and quickly run analytics. But there is a way to turn those heaps of data into actionable insights to get clearer answers to your biggest questions and better drive your firm’s strategy. Read the blog to learn how to improve your back end to go from data hoarding to decision-making.

The Internet of Things (IoT) didn’t just connect everything everywhere; It laid the groundwork for the next industrial revolution.
Connected devices sending data was only one achievement of the IoT—but one that helped solve the problem of data spread across countless silos that was not collected because it was too voluminous and/or too expensive to analyze.
Now, with advances in cloud computing and analytics, cheaper and more scalable factory solutions are available. This, in combination with the cost and size of sensors continuously being reduced, supplies the other achievement: the possibility for every organization to digitally transform.
Using a Smart Factory system, all relevant data is aggregated, analyzed, and acted upon. Sensors, devices, people, and processes are part of a connected ecosystem providing:
• Reduced downtime
• Minimized surplus and defects • Deep insights
• End-to-end real-time visibility

Infosys has been recognized as a ‘Leader’ in NelsonHall’s Vendor Evaluation and Assessment (NEAT) report on big data and analytics services 2018.We have also been highly rated for our focus on automation. Our ability to meet future client requirements as well as deliver immediate benefits such as analytics, data management and support functions to our clients with a specific focus on process automation enabled us to secure this position.

A Java application that will successfully be able to retrieve, insert & delete data from our database which will be implemented in HBase along with.Basically the idea is to provide much faster, safer method to transmit & receive huge amounts of data

As of May 25, 2018, organizations around the world—not just those based in the EU—need to be prepared to meet the requirements outlined within the EU General Data Protection Regulation (GDPR). Those requirements apply to any organization doing business with any of the more than 700 million EU residents, whether or not it has a physical presence in the EU.
IBM® Security can help your organization secure and protect personal data with a holistic GDPR-focused Framework that includes software, services and GDPR-specific tools. With deep industry expertise, established delivery models and key insights gained from helping organizations like yours navigate complex regulatory environments, IBM is well positioned to help you assess your needs, identify your challenges and get your GDPR program up and running.

Organizations are faced with providing secure authentication, authorization, and Single Sign On (SSO) access to thousands of users accessing hundreds of disparate applications. Ensuring that each user has only the necessary and authorized permissions, managing the user’s identity throughout its life cycle, and maintaining regulatory compliance and auditing further adds to the complexity. These daunting challenges are solved by Identity and Access Management (IAM) software.
Traditional IAM supports on-premises applications, but its ability to support Software-as-a-Service (SaaS)-based applications, mobile computing, and new technologies such as Big Data, analytics, and the Internet of Things (IoT) is limited. Supporting on-premises IAM is expensive, complex, and time-consuming, and frequently incurs security gaps.
Identity as a Service (IDaaS) is an SaaS-based IAM solution deployed from the cloud. By providing seamless SSO integration to legacy on-premises applications and modern cloud-

There’s strong evidence organizations are challenged by the opportunities presented by external information sources such as social media, government trend data, and sensor data from the Internet of Things (IoT). No longer content to use internal databases alone, they see big data resources augmented with external information resources as what they need in order to bring about meaningful change. According to a September 2015 global survey of 251 respondents conducted by Harvard Business Review Analytic Services, 78 percent of organizations agree or strongly agree that within two years the use of externally generated big data will be “transformational.” But there’s work to be done, since only 21 percent of respondents strongly agree that external data has already had a transformational effect on their firms.

Learn how CIOs can set up a system infrastructure for their business to get the best out of Big Data. Explore what the SAP HANA platform can do, how it integrates with Hadoop and related technologies, and the opportunities it offers to simplify your system landscape and significantly reduce cost of ownership.

The bar has been raised higher than ever, and the role of IT is evolving to meet it. As a result, IT must support applications and services that make it possible for the business to provide new, diverse customer experiences while generating expanding revenues via the emergent crown jewels of business: big data, cloud, and mobility.
Read on to find out more.

Big data and analytics is a rapidly expanding field of information technology. Big data incorporates technologies and practices designed to support the collection, storage, and management of a wide variety of data types that are produced at ever increasing rates. Analytics combine statistics, machine learning, and data preprocessing in order to extract valuable information and insights from big data.

The competitive advantages and value of BDA are now widely acknowledged and have led to the shifting of focus at many firms from “if and when” to “where and how.” With BDA applications requiring more from IT infrastructures and lines of business demanding higher-quality insights in less time, choosing the right infrastructure platform for Big Data applications represents a core component of maximizing value. This IDC study considered the experiences of firms using Cisco UCS as an infrastructure platform for their BDA applications. The study found that Cisco UCS contributed to the strong value the firms are achieving with their business operations through scalability, performance, time to market, and cost effectiveness. As a result, these firms directly attributed business benefits to the manner in which Cisco UCS is deployed in the infrastructure.

Marketing as you know it will never be the same. There’s a fundamental shift in relationships between brands and customers—fueled by smartphones, social media, and today’s
always-on, always-connected mentality. Marketers have access
to more customer data (big data) than ever before. But the quantity of data only matters if you’re smart about using it—to power 1:1 customer journeys.

If your business is like most, you are grappling with data storage. In an annual Frost & Sullivan survey of IT decision-makers, storage growth has been listed among top data center challenges for the past five years.2 With businesses collecting, replicating, and storing exponentially more data than ever before, simply acquiring sufficient storage capacity is a problem.
Even more challenging is that businesses expect more from their stored data. Data is now recognized as a precious corporate asset and competitive differentiator: spawning new business models, new revenue streams, greater intelligence, streamlined operations, and lower costs. Booming market trends such as Internet of Things and Big Data analytics are generating new opportunities faster than IT organizations can prepare for them.

From its conception, this special edition has had a simple goal: to help SAP customers better understand SAP HANA and determine how they can best leverage this transformative technology in their organization. Accordingly, we reached out to a variety of experts and authorities across the SAP ecosystem to provide a true 360-degree perspective on SAP HANA.

This TDWI Checklist Report presents requirements for analytic DBMSs with a focus on their use with big data. Along the way, the report also defines the many techniques and tool types involved. The requirements checklist and definitions can assist users who are currently evaluating analytic databases and/or developing strategies for big data analytics.

For years, experienced data warehousing (DW) consultants and analysts have advocated the need for a well thought-out architecture for designing and implementing large-scale DW environments. Since the creation of these DW architectures, there have been many technological advances making implementation faster, more scalable and better performing. This whitepaper explores these new advances and discusses how they have affected the development of DW environments.

New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose built platforms more capable of meeting the real-time needs of a more demanding end user and the opportunities presented by Big Data. Significant strategy shifts are under way to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support Big Data and real-time needs of innovative enterprises companies.

This white paper discusses the issues involved in the traditional practice of deploying transactional and analytic applications on separate platforms using separate databases. It analyzes the results from a user survey, conducted on SAP's behalf by IDC, that explores these issues.

The technology market is giving significant attention to Big Data and analytics as a way to provide insight for decision making support; but how far along is the adoption of these technologies across manufacturing organizations? During a February 2013 survey of over 100 manufacturers we examined behaviors of organizations that measure effective decision making as part of their enterprise performance management efforts. This Analyst Insight paper reveals the results of this survey.